We propose a novel approach to 3D hand geometry based person authentication using projected light patterns. Instead of explicitly computing a depth map of the palm for recognition, we capture the depth information in the deformations of a projected texture pattern, and use it directly for recognition. The deformed pattern is characterized using local texture measures, which can encode the certain depth characteristics of the palm. An authentication system built using the proposed technique achieves an equal error rate of 0.84% on a dataset of 1341 samples collected from 149 users, as opposed to 4.03% using traditional 2D features. on an identical dataset. The approach is robust as well as computationally efficient and could be applied to other 3D object recognition problems as well.